Search Results (137)

Cementation using Ordinary Portland Cement (OPC) remains the standard method for conditioning low- and intermediate-level radioactive waste, including Spent Ion Exchange Resins (SIERs). This work presents an integrated strategy involving thermal pretreatment to minimize waste volume and eliminate organic constituents, followed by encapsulation within three distinct binders: CEM I, CEM III, and a novel one-part geopolymer. The one-part geopolymer system represents a significant operational innovation, enabling safe and simple “just-add-water” processing and avoiding the need to handle alkaline solutions. The proposed geopolymer, synthesized from metakaolin, blast furnace slag, and solid sodium silicate, was systematically benchmarked against conventional OPC matrices (CEM I, CEM III) by assessing their capacity to immobilize thermally treated SIER ashes under accelerated leaching conditions. For benchmarking, leaching indices for Cs and Sr were determined following the ANSI/ANS 16.9 standard protocol in three representative environments simulating operational and long-term repository scenarios, providing a quantitative evaluation of radionuclide retention and matrix durability. Results indicate that the one-part geopolymer improved leaching indices for Cs and Sr compared to both cementitious binders and complied with regulatory waste acceptance criteria. The comparative results highlight the potential of geopolymer technology to increase waste loading efficiencies and improve long-term safety, establishing a robust framework for future radioactive waste management approaches. Full article

This paper presents a resilient and energy-efficient framework for jamming mitigation in cluster-based wireless sensor networks (WSNs), addressing a critical vulnerability in hostile or interference-prone environments. The proposed approa ch integrates dynamic cluster reorganization, adaptive MAC-layer behavior, and multipath routing strategies to restore communication capabilities and sustain network functionality under jamming conditions. The framework is evaluated across heterogeneous topologies using Zigbee and Bluetooth Low Energy (BLE); both stacks were validated in a physical testbed with matched jammer and traffic conditions, while simulation was used solely to tune parameters and support sensitivity analyses. Results demonstrate significant improvements in Packet Delivery Ratio, end-to-end delay, energy consumption, and retransmission rate, with BLE showing particularly high resilience when combined with the mitigation mechanism. Furthermore, a comparative analysis of routing protocols including AODV, GAF, and LEACH reveals that hierarchical protocols achieve superior performance when integrated with the proposed method. This framework has broader applicability in mission-critical IoT domains, including environmental monitoring, industrial automation, and healthcare systems. The findings confirm that the framework offers a scalable and protocol-agnostic defense mechanism, with potential applicability in mission-critical and interference-sensitive IoT deployments. Full article

The research work presents an artificial intelligence-driven, energy-aware data aggregation and routing protocol for wireless sensor networks (WSNs) with the primary objective of extending overall network lifetime. The proposed scheme leverages reinforcement learning in conjunction with deep Q-networks (DQNs) to adaptively optimize both Cluster Head (CH) selection and routing decisions. An adaptive clustering mechanism is introduced wherein factors such as residual node energy, spatial proximity, and traffic load are jointly considered to elect suitable CHs. This approach mitigates premature energy depletion at individual nodes and promotes balanced energy consumption across the network, thereby enhancing node sustainability. For data forwarding, the routing component employs a DQN-based strategy to dynamically identify energy-efficient transmission paths, ensuring reduced communication overhead and reliable sink connectivity. Performance evaluation, conducted through extensive simulations, utilizes key metrics including network lifetime, total energy consumption, packet delivery ratio (PDR), latency, and load distribution. Comparative analysis with baseline protocols such as LEACH, PEGASIS, and HEED demonstrates that the proposed protocol achieves superior energy efficiency, higher packet delivery reliability, and lower packet losses, while adapting effectively to varying network dynamics. The experimental outcomes highlight the scalability and robustness of the protocol, underscoring its suitability for diverse WSN applications including environmental monitoring, surveillance, and Internet of Things (IoT)-oriented deployments. Full article

WSNs consist of numerous energy-constrained Sensor Nodes (SNs), making energy efficiency a critical challenge. This paper presents a novel multipath routing model designed to enhance network lifetime by simultaneously optimizing energy consumption, node connectivity, and transmission distance. The model employs an Improved Particle Swarm Optimization (IPSO) algorithm to dynamically determine the optimal weight coefficients of a cost function that integrates three parameters: residual energy, link reliability, and buffer capacity. A compressed Bloom filter is incorporated to improve packet transmission efficiency and reduce error rates. Simulation experiments conducted in the NS2 environment show that the proposed approach significantly outperforms existing protocols, including Reinforcement Learning Q-Routing Protocol (RL-QRP), Low Energy Adaptive Clustering Hierarchical (LEACH), On-Demand Distance Vector (AODV), Secure and Energy-Efficient Multipath (SEEM), and Energy Density On-demand Cluster Routing (EDOCR), achieving a 7.45% reduction in energy consumption and maintaining a higher number of active nodes over time. Notably, the model sustains 19 live nodes at round 800, whereas LEACH and APTEEN experience complete node depletion by that point. This adaptive, energy-aware routing strategy improves reliability, prolongs operational lifespan, and enhances load balancing, making it a promising solution for real-world WSN applications. Full article

This work compares reactive (castor) and non-reactive (rapeseed, sunflower, linseed, and used cooking) oils, each at a dosage of 10 wt%, when incorporated into an in-house two-component polyurethane (PU) parquet adhesive. A commercial market adhesive was tested only as an external benchmark and was not modified. Mechanical properties were evaluated according to EN ISO 17178, inorganic leaching according to EN 12457-4, and volatile organics were screened by headspace GC–MS (not comparable to ISO 16000-9 chamber protocols). All in-house formulations met the EN ISO 17178 acceptance limits. The sunflower oil variant showed the highest shear strength, whereas rapeseed and castor oils provided stable tensile performance. HS-GC-MS did not yield high-confidence VOC identifications; therefore, no regulatory emission claim is made. The formulation with used cooking oil exhibited the largest variability and elevated leaching of Zn and Sb, underscoring the need for feedstock quality control. At 10 wt% loading, standard-compliant performance was obtained with both reactive and non-reactive oils, suggesting that physical modification can be sufficient, while castor oil may additionally react. In contrast to derivatized oils reported elsewhere, our approach employs unmodified oils, thereby avoiding extra reaction steps—such as epoxidation, hydroxylation, and transesterification—that typically increase the carbon footprint, while still meeting relevant standards. Full VOC chamber testing and LCA are beyond the scope of this study. Full article

WSNs are an important component of the Internet of Things (IoT), and the research on their routing protocols has always been a hot topic in academia. However, in ARTFMRs’ collaborative operation along railway lines, there are common problems such as energy holes, high latency, and uneven energy consumption in LWSNs. To address these issues, this paper proposes a genetic algorithm-optimized energy-aware routing protocol (GAECRPQ). Firstly, a non-uniform deployment strategy of three-line isosceles triangles is constructed to enhance coverage and balance node distribution. Secondly, an energy–distance adaptive weighting mechanism based on a genetic algorithm is introduced for cluster head (CH) selection to reduce energy consumption in hotspots and extend the network lifetime. Finally, a task-aware TDMA dynamic time slot allocation method is proposed, which incorporates the real-time task status of ARTFMRs into communication scheduling to achieve priority transmission under latency constraints. The simulation results show, that compared with six unequal clustering protocols—EADUC, EAUCA, EBUC, EEUC, LEACH, and LEACH-C—the three-line isosceles triangle deployment has a wider coverage area, and the GAECRPQ protocol increases the network lifetime by 7.4%, the lifetime by 40%, and reduces the average latency by 55.77%, 53.07%, 47.61%, 39.87%, 52.08%, and 50.48%, respectively. This verifies that GAECRPQ has good performance in terms of network lifetime and energy utilization efficiency, providing a practical solution for the collaborative operation of ARTFMRs in railway maintenance scenarios. Full article

This article presents a study of the energy efficiency of a wireless sensor network for measuring the main physicochemical parameters of soil. The main physicochemical parameters of soil are measured—acidity and electrical conductivity. The study on the transmission of measured data on the main soil parameters is conducted through simulation, with program modules developed in the MATLAB environment. Four main protocols for data routing are studied—the LEACH (Low-Energy Adaptive Clustering Hierarchy), EAMMH (Energy-Aware Multi-Hop Multi-Path Hierarchical), SEP (Stable Election Protocol for clustered heterogeneous WSN), and TEEN (Threshold-sensitive Energy Efficient Network). The results of the main energy indicators are obtained and a comparative analysis of the two protocols is carried out. The results obtained show that the SEP and TEEN routing protocols have better performance and efficiency with respect to inactive nodes in the network compared to the other two protocols. The EAMMH and LEACH routing protocols are the best in terms of the energy consumption by sensors in the network. Full article

Wireless Sensor Networks (WSNs) are very important for monitoring complex 3D environments like forests, where energy efficiency and reliable communication are critical. This paper presents EEL-GA, an Energy Efficient LEACH-based clustering protocol optimized using a Genetic Algorithm. Cluster head (CH) selection is guided by a dual-metric fitness function combining residual energy and intra-cluster distance. EEL-GA is evaluated against EEL variants using Particle Swarm Optimization (PSO), Differential Evolution (DE), and the Artificial Bee Colony (ABC) across key performance metrics, including energy efficiency, packet delivery, and cluster lifetime. Simulations using real environmental data confirm EEL-GA’s superiority in sustaining energy, minimizing delay, and improving network stability, making it ideal for smart forestry and mission-critical WSN deployments. The model also incorporates environmental dynamics, such as temperature and humidity, enhancing its robustness in real-world applications. These findings support EEL-GA as a scalable, adaptive solution for future energy-aware 3D WSN frameworks. Full article

Plastic pollution in freshwater ecosystems is an increasing environmental concern, prompting the search for biodegradable polymer (BP) alternatives. However, their degradation in natural aquatic environments remains poorly investigated and understood. This four-month in situ study compared the degradation in a lentic freshwater ecosystem of two compostable items, Mater-Bi^® shopping bag and disposable dish, with their respective pure polymer matrices, poly(butylene adipate-co-terephthalate) (PBAT) and polylactic acid (PLA). Additionally, biodegradable poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) and oil-based polypropylene (PP) were also tested. Changes in morphology, chemical composition and thermal and mechanical properties, as well as microbial colonization, were analyzed over time. A validated cleaning protocol was employed to ensure accurate surface analysis. Results showed detectable but limited degradation of pure polymers and their matrices in commercial products after 120 days of immersion with variations observed among polymer materials. Compostable materials exhibited significant leaching of fillers (starch, inorganic particles), leading to morphological changes and fragmentation. PHBV showed the fastest degradation among tested polyesters. PP exhibited only minor surface changes. Microbial colonization varied with polymer structure and degradability, but long-term degradation was limited by polymer properties and the gradual development of the plastisphere. This study highlights that standard laboratory tests may overestimate the environmental degradability of BPs and emphasizes the importance of in situ assessments, careful cleaning procedures and property characterizations to accurately assess polymer degradation in freshwater systems. Full article

Numerous protocols have emerged to address the energy depletion problem in Wireless Sensor Networks (WSNs). Among these protocols, the Dynamic Multi-Hop Routing (DMR) protocol adopts a dynamic technique for routing data across the network. The use of the DMR protocol has shown promising results in reducing energy consumption, prolonging the network lifetime, and increasing throughput. To improve the performance of WSNs, this paper proposes the Enhanced Dynamic Multi-Hop Routing (EDMR) protocol as a modification of the DMR protocol. The EDMR protocol introduces an effective sleeping mechanism that selectively deactivates clusters that do not generate significantly updated data for a specific duration. This mechanism reduces redundant transmissions, thereby saving energy and prolonging the network lifetime. The EDMR protocol incorporates static and dynamic approaches to support two major categories of applications: monitoring and event-driven applications. The proposed protocol is evaluated against the DMR protocol, the Enhanced Dynamic Multi-Hop Technique (EMDHT-LEACH) protocol, and the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The simulation results demonstrate that the EDMR protocol mitigates energy depletion, extends the network lifetime, increases stability, and improves network throughput toward the Base Station (BS), while reducing packet redundancy compared with the other protocols. Full article

Mining by-products present both an environmental challenge and a resource opportunity. This review investigates their potential application in road pavement construction, focusing on materials such as fly ash, slag, sulphur, red mud, tailings, and silica fume. Drawing from laboratory and field studies, the review examines their roles across pavement layers—subgrade, base, subbase, asphalt mixtures, and rigid pavements—emphasising mechanical properties, durability, moisture resistance, and ageing performance. When properly processed or stabilised, many of these wastes meet or exceed conventional performance standards, contributing to reduced use of virgin materials and greenhouse gas emissions. However, issues such as variability in composition, leaching risks, and a lack of standardised design protocols remain barriers to adoption. This review aims to consolidate current research, evaluate practical feasibility, and identify directions for future studies that would enable the responsible and effective reuse of mining waste in transportation infrastructure. Full article

Sustainable agriculture and food security are challenged by the indiscriminate use of synthetic nitrogen (N₂) fertilizers, inefficient water management, and land degradation. Hydroponic cultivation uses nutrient-rich aqueous media and is a climate-resilient and resource-efficient alternative to traditional farming methods, whose dependence on synthetic N₂ fertilizers reduces their long-term sustainability. Biological nitrogen fixation (BNF), which is mediated by diazotrophs that reduce atmospheric N₂ to plant-available ammonium, has emerged as a sustainable alternative to synthetic N₂ input in hydroponic systems. This review discusses the integration of BNF into hydroponic systems by exploring the functional diversity of diazotrophs, root–microbe interactions, and environmental constraints. It further highlights recent advances in strain improvement, microbial consortia development, nitrogenase protection, and genome editing tools, novel bioformulation strategies to enhance microbial compatibility with hydroponic nutrient regimes, and omics-based tools for the real-time assessment of N₂ fixation and microbial functionality. Key challenges, such as microbial leaching, nitrate-induced inhibition of nitrogenase activity, and the absence of standardized biostimulant protocols, are discussed. Case studies on staple crops have demonstrated enhanced NUE and yield productivity following diazotroph applications. This review concludes with future perspectives on synthetic biology, regulatory policies, and omics-based tools for the real-time assessment of N₂ fixation and microbial functionality. Full article

The growing demand for rare earth elements (REEs) in high-tech and green energy sectors has prompted renewed exploration of unconventional sources. Drill cuttings, which are commonly discarded during subsurface drilling, are increasingly recognized as a potentially valuable, underutilized secondary REE reservoir. This review adopts a mineral-first lens to assess REE occurrence, extractability, and recovery strategies from drill cuttings across various lithologies. Emphasis is placed on how REEs associate with specific mineral host phases ranging from ion-adsorbed clays and organically bound forms to structurally integrated phosphates, each dictating distinct leaching pathways. The impact of drilling fluids on REE surface chemistry and mineral integrity is critically examined, alongside an evaluation of analytical and extraction methods tailored to different host phases. A scenario-based qualitative techno-economic assessment and a novel decision-tree framework are introduced to align mineralogy with optimal recovery strategies. Limitations in prior studies, particularly in characterization workflows and mineralogical misalignment in leaching protocols, are highlighted. This review redefines drill cuttings from industrial waste to a strategic resource, advocating for mineralogically guided extraction approaches to enhance sustainability in the critical mineral supply chain. Full article

Entomopathogenic fungus-based biopesticides are an excellent alternative to synthetic pesticides and are widely used in insect pest control. With the transformations of the agri-food system, it is important to consider the One Health approach, which recognizes that health threats are shared at the interface between people, animals, plants, and the environment. The safety and environmental impact of fungi-based insecticides should be assessed comprehensively, taking into account not only their effects on non-target organisms and human health but also their environmental fate. This includes how these substances degrade, persist, or dissipate in soil, water, and air and their potential to bioaccumulate or leach into groundwater. Such assessments are essential to ensure that their long-term use does not pose unintended risks to ecosystems or public health. This systematic review aims to identify and analyze available studies on the potential One Health hazards associated with fungal biopesticides. A total of 134 articles were selected: 84 bioassay articles (63%), 36 case reports (27%), 10 field studies (7%), and 4 other types of studies (3%). Of these articles, 59 were studies on vertebrate animals and 65 studies on invertebrate animals, 6 studies on diverse organisms, 2 studies focused specifically on risk assessment for non-target organisms in the environment, while 2 other studies looked at the toxicological hazards associated with human exposure to the metabolites of the fungus present in air. The United States had the highest number of publications (33). Beauveria bassiana and Metarhizium anisopliae followed by the fungi Cordyceps fumosorosea (Paecilomyces fumosoroseus) and B. brongniartii were the most prevalent fungal species in the studies. This review highlights that case reports of infections in humans and other vertebrates by fungi are not related to the use of fungal biopesticides. A predominance of studies with bees was identified due to the importance of these insects as pollinators. The findings indicate that fungal biopesticides pose minimal risks when used appropriately. Nevertheless, the necessity for standardized safety assessments is emphasized. In order to ensure greater effectiveness, it is essential to develop unified protocols and bioassays with specific risk indicators aligned with the One Health approach. This includes evaluating potential effects on pollinators, vertebrate toxicity, and the environmental persistence of metabolites. In future research, the development of integrated guidelines that simultaneously consider human, animal, and environmental health is recommended. Full article

Wireless sensor networks face challenges such as energy consumption, scalability, security vulnerabilities, and communication range limitations, impacting their overall performance and reliability. To resolve these problems, energy-efficient protocols and adaptive sleep modes are implemented in wireless sensor networks (WSNs). Actually, LEACH clustering is widely regarded as one of the primary strategies to extend the lifetime of WSNs. However, clustering does not always guarantee optimal performance. In this paper, we demonstrate that clustering effectiveness is contingent on specific conditions related to several key parameters, including cluster density and the distance of nodes from the base station. Our research presents a mathematically validated analysis, supported by simulation results, that illustrates how clustering can enhance WSN performance, particularly in terms of network lifetime, throughput, and the timing of the first, middle, and last node deaths. Our findings indicate that LEACH is inefficient when nodes are within 80 m of the base station. Furthermore, clusters’ densities are related directly to the distance to the base station. Specifically, for distances less than 80 m, nodes should send their data individually; for distances between 83 and 123 m, a cluster density of two is most effective; and for distances between 123 and 149 m, the optimal density increases to three nodes. Full article